class_docstr: An artifact backend for Google Cloud Storage (GCS).
  
  Args:
      bucket_name:
          The name of the bucket to store artifacts.
  
      client:
          A google-cloud-storage `Client` to use for storage operations. If not specified, a new
          client will be created with default settings.
  
  Example:
      .. code-block:: python
  
          import optuna
          from optuna.artifacts import GCSArtifactStore, upload_artifact
  
  
          artifact_backend = GCSArtifactStore("my-bucket")
  
  
          def objective(trial: optuna.Trial) -> float:
              ... = trial.suggest_float("x", -10, 10)
              file_path = generate_example(...)
              upload_artifact(trial, file_path, artifact_backend)
              return ...
  
      Before running this code, you will have to install `gcloud` and run
  
      .. code-block:: bash
  
          gcloud auth application-default login
  
      so that the Cloud Storage library can automatically find the credential.
code: def write(self, artifact_id: str, content_body: "BinaryIO") -> None:
      blob = self.bucket_obj.blob(artifact_id)
      data = content_body.read()
      blob.upload_from_string(data)
  
file_path: optuna/optuna/artifacts/_gcs.py
imports: from __future__ import annotations
  from io import BytesIO
  from typing import TYPE_CHECKING
  from optuna._experimental import experimental_class
  from optuna._imports import try_import
  from optuna.artifacts.exceptions import ArtifactNotFound
label_desc: Use image node_id 3 for calling the GCSArtifactStore obj's underlying member method code with example usage: obj.write(artifact_id, content_body) without return types